Eight‐week antidepressant treatment reduces functional connectivity in first‐episode drug‐naïve patients with major depressive disorder

重性抑郁障碍 抗抑郁药 默认模式网络 毒品天真 依西酞普兰 静息状态功能磁共振成像 心理学 神经影像学 西酞普兰 功能连接 精神科 内科学 医学 神经科学 药品 心情 焦虑
作者
Le Li,Yun‐Ai Su,Yankun Wu,F. Xavier Castellanos,Ke Li,Jitao Li,Tianmei Si,Chao‐Gan Yan
出处
期刊:Human Brain Mapping [Wiley]
卷期号:42 (8): 2593-2605 被引量:51
标识
DOI:10.1002/hbm.25391
摘要

Previous neuroimaging studies have revealed abnormal functional connectivity of brain networks in patients with major depressive disorder (MDD), but findings have been inconsistent. A recent big-data study found abnormal intrinsic functional connectivity within the default mode network in patients with recurrent MDD but not in first-episode drug-naïve patients with MDD. This study also provided evidence for reduced default mode network functional connectivity in medicated MDD patients, raising the question of whether previously observed abnormalities may be attributable to antidepressant effects. The present study (ClinicalTrials.gov identifier: NCT03294525) aimed to disentangle the effects of antidepressant treatment from the pathophysiology of MDD and test the medication normalization hypothesis. Forty-one first-episode drug-naïve MDD patients were administrated antidepressant medication (escitalopram or duloxetine) for 8 weeks, with resting-state functional connectivity compared between posttreatment and baseline. To assess the replicability of the big-data finding, we also conducted a cross-sectional comparison of resting-state functional connectivity between the MDD patients and 92 matched healthy controls. Both Network-Based Statistic analyses and large-scale network analyses revealed intrinsic functional connectivity decreases in extensive brain networks after treatment, indicating considerable antidepressant effects. Neither Network-Based Statistic analyses nor large-scale network analyses detected significant functional connectivity differences between treatment-naïve patients and healthy controls. In short, antidepressant effects are widespread across most brain networks and need to be accounted for when considering functional connectivity abnormalities in MDD.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
他说发布了新的文献求助10
刚刚
wanci应助鲸luo采纳,获得10
1秒前
1秒前
耍酷慕梅完成签到 ,获得积分10
2秒前
黑皮小白完成签到,获得积分10
2秒前
3秒前
思源应助宇宙停止膨胀采纳,获得10
4秒前
5秒前
pxin发布了新的文献求助10
6秒前
大神瓜完成签到,获得积分10
8秒前
8秒前
兴奋芷完成签到,获得积分10
8秒前
11秒前
11秒前
乘风发布了新的文献求助10
11秒前
爆米花应助XY采纳,获得10
11秒前
12秒前
12秒前
13秒前
难过的研究牲完成签到 ,获得积分10
13秒前
14秒前
Teen发布了新的文献求助10
14秒前
xlong发布了新的文献求助20
16秒前
xudaniel完成签到,获得积分10
16秒前
pxin完成签到,获得积分10
16秒前
肚子藤完成签到,获得积分10
17秒前
17秒前
田様应助跳跃苗条采纳,获得10
17秒前
蟹黄包发布了新的文献求助10
17秒前
让我多睡会吧完成签到,获得积分20
19秒前
drchen完成签到 ,获得积分10
20秒前
v0id应助钟贵泉采纳,获得10
21秒前
hahah发布了新的文献求助10
21秒前
HD完成签到,获得积分20
23秒前
23秒前
23秒前
26秒前
木马完成签到,获得积分10
26秒前
小马甲应助科研通管家采纳,获得10
26秒前
NexusExplorer应助科研通管家采纳,获得10
26秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
China Pluperfect I: Epistemology of Past and Outside in Chinese Art 520
Matrix Methods in Data Mining and Pattern Recognition Second Edition 510
Governing Growth: Us Industrial Policy from Hamilton to Trump 500
The fast track to determining transfer functions of linear circuits: The student guide 500
The Analytical and Numerical Solution of Electric and Magnetic Fields 500
Synthesis of P-Chiral Phosphine Ligands and Their Applications in Asymmetric Catalysis 400
热门求助领域 (近24小时)
化学 材料科学 医学 生物 纳米技术 工程类 有机化学 化学工程 生物化学 计算机科学 内科学 物理 复合材料 催化作用 细胞生物学 无机化学 光电子学 物理化学 电极 基因
热门帖子
关注 科研通微信公众号,转发送积分 7624124
求助须知:如何正确求助?哪些是违规求助? 9199281
关于积分的说明 19722241
捐赠科研通 7195342
什么是DOI,文献DOI怎么找? 3273475
关于科研通互助平台的介绍 2435663
邀请新用户注册赠送积分活动 2269253